Improved Binarization Algorithm of DM Code Image under Complex Illumination

The DM (Data Matrix) two-dimensional barcode images collected on metal parts with complex lighting conditions are prone to low contrast and local shadow, and the problem of uneven brightness leads to the loss of two-dimensional barcode information, which brings difficulties to the subsequent processing. However, the existing binarization algorithms will have the problems of too much noise and long segmentation time when dealing with this kind of images. To solve these problems, an improved local threshold algorithm is proposed to improve the anti-noise performance and computational efficiency. First of all, the algorithm model is improved to reduce the sensitivity to noise, and then the integral image algorithm is used to speed up the calculation of the local mean. In addition, the gray value of the local central pixel and the local mean are used to adjust the threshold adaptively according to the gray change characteristics of each pixel neighborhood, so as to further improve the segmentation efficiency. The improved local threshold algorithm and other five algorithms are tested on images with complex illumination conditions. The results show that the improved local threshold algorithm can not only effectively overcome the influence of complex illumination, has a good anti-noise effect, but also greatly shorten the time of image segmentation.